Probabilistic Robotics with Applications To Navigation
Sebastian Thrun, Prof. of Computer Science, Stanford Univ.
Tuesday, November 21, 2006|
4:00pm - 5:30pm
CHANGE IN LOCATION: Toyota Tech. Center
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|CHANGE IN LOCATION: Directions: The talk will be at: Toyota Technical Center 2350 Green Road, Suite 101 Ann Arbor, MI 48105 Google maps link: http://maps.google.com/mapsf=q&hl=en&q=2350+Green+Road,+Ann+Arbor&ie=UTF8&z A more detailed map of the area is attached to this email, or is available at http://www.eecs.umich.edu/~ddolgov/ttc_directions.pdf|
About the Event
NOTE CHANGE IN LOCATION: TOYOTA TECHNICAL CENTER Bayesian techniques have often been heralded as the most significant innovation in robotics software over the past decade. Probabilistic techniques model the inherent uncertainty in our models of the world, and they also model the inherent uncertainty in sensor data. As such, they tend to be superior to many classical techniques that ignore uncertainty in our world models, and they are superior to many reactive techniques that ignore the uncertainty in sensor data. This talk will introduce the audience into a rich body of work in the area of robotic navigation, mapping, and localization, and discuss recent work on precision localization of self-driving cars.
Contact: David Wingate
Sponsor(s): AI Seminar Series
Open to: Public